NLP at SemEval-2019 Task 6: Detecting Offensive language using Neural Networks
Prashant Kapil, Asif Ekbal, Dipankar Das · 2019
In this paper we built several deep learning architectures to participate in shared task Of-fensEval: Identifying and categorizing Offensive language in Social media by semEval-2019 (Zampieri et al., 2019b).The dataset was annotated with three level annotation schemes and task was to detect between offensive and not offensive, categorization and target identification in offensive contents.Deep learning models with POS information as feature were also leveraged for classification.The three best models that performed best on individual sub tasks are stacking of CNN-Bi-LSTM with Attention, BiLSTM with POS information added with word features and Bi-LSTM for third task.Our models achieved a Macro F1 score of 0.7594, 0.5378 and 0.4588 in Task(A,B,C) respectively with rank of 33 rd , 54 th and 52 nd out of 103, 75 and 65 submissions.